Title :
Firm Bankruptcy Prediction: Experimental Comparison of Isotonic Separation and Other Classification Approaches
Author :
Ryu, Young U. ; Yue, Wei T.
Author_Institution :
Univ. of Texas, Richardson, TX, USA
Abstract :
A newly introduced method called isotonic separation is evaluated in the prediction of firm bankruptcy. Feature reduction methods are first applied to reduce the ratios used in the prediction. Then, various classification methods, including discriminant analysis, neural networks, decision tree induction, learning vector quantization, rough sets, and isotonic separation, are used with the reduced ratios. Experiments show that the isotonic separation method is a viable technique, performing generally better than other methods for short-term bankruptcy prediction.
Keywords :
decision trees; financial management; neural nets; rough set theory; vector quantisation; decision tree induction; discriminant analysis; feature reduction; firm bankruptcy prediction; isotonic separation; learning vector quantization; neural network; rough sets; Classification tree analysis; Decision trees; Helium; Linear programming; Marketing and sales; Neural networks; Pattern classification; Prediction methods; Rough sets; Vector quantization; Bankruptcy prediction; isotonic separation; pattern classification; prediction method;
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
DOI :
10.1109/TSMCA.2005.843393